Data processing systems and methods implementing improved analytics platform and networked information systems

Abstract

An analytics platform and architecture is disclosed that improves the capture, extraction, and reporting of data required for certain measures, provides real-time data surveillance, dashboards, tracking lists, and alerts for specific, high-priority data, and offers dynamic, ad-hoc reporting capabilities. The platform includes a data extraction facility that gathers data from numerous sources, a data mapping facility that identifies and maps key data elements and links data over time, a data normalization facility to normalize the data and, optionally, de-identify the data, a flexible data warehouse for storing raw data or longitudinal data, an analytics facility for data mining, analytic model building, risk identification, benchmarking and tracking. The improved platform and architecture integrates social networking technology and analysis (SNA) on data to cluster data for more efficient, technically improved and focused processing.

What is claimed is: 
     
       1. An analytics platform comprising:
 at least one processor; 
 a data extraction facility extracting heterogeneous data from a plurality of data sources and normalizing said heterogenous data and storing it as homogenous data in a homogenous data base; 
 a rules database storing rules executed by the at least one processor mapping normalized homogenous data elements to heterogenous terminologies; 
 a graph database receiving selected ones of said normalized homogenous data elements and storing said selected ones of said normalized homogenous data elements as nodes and edges information defining relationships between said selected ones of said normalized homogenous data elements; and 
 social networking tools receiving at least one of nodes and edges information from said graph database, said social networking tools identifying clusters of nodes based on rules applied to said at least one of nodes and edges information from said graph database. 
 
     
     
       2. The analytics platform of  claim 1  wherein said rules applied to said at least one of nodes and edges information from said graph database includes said edges having an edge weight. 
     
     
       3. The analytics platform of  claim 1  wherein said rules applied to said at least one of nodes and edges information from said graph database includes said edges having an edge weight more than a specified amount or within a specified range. 
     
     
       4. The analytics platform of  claim 1  further including at least one database management system querying the homogenous database using Structured Query Language (SQL) to obtain said selected ones of said normalized homogenous data elements to store said selected ones of said normalized homogenous data elements in said graph database. 
     
     
       5. The analytics platform of  claim 1  wherein each of said nodes in said graph database has a unique identifier. 
     
     
       6. The analytics platform of  claim 1  wherein said graph database includes capabilities for additional attributes to be assigned to nodes and edges in said graph database. 
     
     
       7. The analytics platform of  claim 1  wherein in said graph database each node is connected with an edge if the node has one or more unique identifiers in common. 
     
     
       8. The analytics platform of  claim 1  further comprising at least one statistics module applying statistical methods to data from said graph database to determine aspects of interest relating to clustered data. 
     
     
       9. An analytics platform comprising:
 at least one processor; 
 computer readable storage medium storing at least one database and instructions that, when executed, cause a computer system to; 
 extract data from the at least one graph database on participants as related to participant service delivery metrics; 
 perform social networking analysis with the extracted data to identify at least one cluster of participants, wherein a cluster is a group of two or more participants having at least one aspect of service delivery in common, and determine the number of the at least one aspect of service delivery shared by the two or more participants; and 
 identify at least one cluster of participants based on at least one of the participant service deliver metrics that is different from other clusters of participants. 
 
     
     
       10. The analytics platform of  claim 9  wherein rules are applied to at least one of nodes and edges information from said graph database, and at least one rule includes said edges having an edge weight. 
     
     
       11. The analytics platform of  claim 10  wherein said rules applied to said at least one of nodes and edges information from said graph database includes said edges having an edge weight more than a specified amount or within a specified range. 
     
     
       12. The analytics platform of  claim 9  further including at least one database management system querying a homogenous database using Structured Query Language (SQL) to obtain selected ones of normalized homogenous data elements to store selected ones of said normalized homogenous data elements in said graph database. 
     
     
       13. The analytics platform of  claim 10  wherein each of said nodes in said graph database has a unique identifier. 
     
     
       14. The analytics platform of  claim 9  wherein said graph database includes capabilities for additional attributes to be assigned to nodes and edges in said graph database. 
     
     
       15. The analytics platform of  claim 9  wherein in said graph database each instance of a node is connected with an edge if the node has one or more unique identifiers in common. 
     
     
       16. An improved data analytics platform comprising:
 at least one processor; and 
 memory storing instructions that, when executed, cause the computing system, to:
 query a database for first data and second data associated with at least one of a geographic region or a service; 
 receive, from the database, a dataset including data records, each data record including a unique identifier, a unique participant identifier, and a specialty of the participant; 
 create a graph in a graph database using the data set, the graph including a node for each unique participant identifier represented in the dataset, the graph further including edges connecting nodes, each edge connecting unique participant identifiers associated with at least one common unique identifier in the dataset, each edge being weighted based on a number of unique identifiers in common; 
 add participant group data to each node of the graph; and 
 use at least one social network analysis algorithm to determine clusters of nodes within the graph. 
 
 
     
     
       17. The improved analytics platform of  claim 16  wherein said first data is clinical data, said second data is claims data, and said participants are physicians. 
     
     
       18. The improved analytics platform of  claim 16  wherein rules are applied to at least one of nodes and edges information from said graph database, and at least one rule includes said edges having an edge weight. 
     
     
       19. The improved analytics platform of  claim 18  wherein said rules applied to said at least one of nodes and edges information from said graph database includes said edges having an edge weight more than a specified amount or within a specified range. 
     
     
       20. The analytics platform of  claim 16  further including at least one database management system querying a homogenous database using Structured Query Language (SQL) to obtain selected ones of normalized homogenous data elements to store selected ones of said normalized homogenous data elements in said graph database.